Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Primary School Students' Perceptions of Artificial Intelligence

Metaphor and Drawing Analysis

Bibliographic Data

ID21445752
AuthorsJale Kalemkuş (0000-0001-7791-9910, Child Development Department Kafkas University Kars Turkey, corresponding author), Fatih Kalemkuş (0000-0001-7218-955X, Distance Education Application and Research Center Kafkas University Kars Turkey)
Year2025
Volume60
Issue1
Publication date2025-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEuropean Journal of Education (JOURNAL)
Journal identifiersISSN: 0141-8211 • E-ISSN: 1465-3435
PublisherWiley (PUBLISHER • GB)
DOI10.1111/ejed.70007
OpenAlexW4406873552
LanguageEN
Citations received7
References cited97

Due to the frequent use of artificial intelligence (AI) technologies in daily life, it is thought that primary school students acquire information about this concept from various sources. The way these sources present AI may affect students' perceptions of AI. In the study, it was aimed to examine the perceptions of third and fourth grade primary school students about AI through metaphors and drawings. This research, which was conducted with the participation of 262 students, was conducted with the phenomenological design. When the metaphors of the participants were analysed, it was determined that they produced 100 metaphors, and these metaphors were evaluated in 17 categories as humanistic feature, information source, danger, development, superhuman feature, service, source of happiness, productivity, orientation, commitment, pervasiveness, necessity, security, speed, difficulty, virtual environment and uncertainty. Accordingly, it was determined that the participants evaluated AI from many different perspectives and produced the most metaphors in the categories of humanistic feature, information source and danger. It was determined that the metaphors human, brain and living were prominent in the human characteristic category; the metaphors teacher, wise and book were prominent in the source of information category; and finally, the metaphors enemy, weapon and monster were prominent in the danger category. When the drawing findings were analysed, it was determined that 37 codes represented four categories: purpose, object, interaction and environment. In the purpose category, service, source of information, and source of happiness; in the object category, mostly humanoid robot; in the interaction category, emphasising interaction; and in the environment category, the environment was not specified. In line with the findings obtained, literature discussions were made and suggestions were made

Linguistics · Mathematics education · Metaphor · Pedagogy · Perception · Primary (astronomy) · Primary education · Sociology · AI in Service Interactions · Psychology · Robotics and Automated Systems · Teaching and Learning Programming

  • Education for sustainability and artificial intelligence based on computational thinking

    Open Access•Jhon Alé, Mariana Rodríguez-Donoso•Discover Education•2026

  • Unpacking the Effects of GenAI on Cultivating Students’ Computational Thinking

    Open Access•Jie Xu, Zexi Chen et al.•Journal of Educational Computing…•2026

  • Children’s visual representations of artificial intelligence (AI)

    Georgios Chionas, Konstantinos Kotsidis•Journal of Research on Technology…•2026

  • Effect of Artificial Intelligence‐Based Tutoring, Cognitive Engagement, and Teacher Feedback on University Students' Academic Performance

    Open Access•Gang Wang, Fang Sun•European Journal of Education•2026

  • Examining the cognitive structures of primary school students regarding the concept of artificial ıntelligence

    Open Access•Nuray Kurtdede Fidan, Feyza Kaleli•The Journal of Educational Research•2026

  • A meta-synthesis study on the use of artificial intelligence in primary education

    Open Access•Seyat Polat, Gürkan Sarıdaş•AI & Society•2026

  • Children's susceptibility to content generated by artificial intelligence

    Open Access•Allison Langer, Steven A Martinez et al.•Technology in Society•2026

  • Corpus Approaches to Critical Metaphor Analysis

    Open Access•Jonathan Charteris-Black, Jonathan Charteris‐black•Corpus Approaches to Critical…•2004

  • Natural language processing

    Open Access•Diksha Khurana, Aditya Koli et al.•Multimedia Tools and Applications•2023

  • Discovering Emotion in Classroom Motivation Research

    Debra K Meyer, Julianne C Turner•Educational Psychologist•2002

  • How phenomenology can help us learn from the experiences of others

    Open Access•Brian E Neubauer, Catherine T Witkop et al.•Perspectives on Medical Education•2019

  • Generative AI

    Open Access•Stefan Feuerriegel, Jochen Hartmann et al.•Business & Information Systems…•2024

  • Risk Perception and Self-Protective Behavior

    Joop Van Der Pligt•European Psychologist•1996

  • Evolution and Revolution in Artificial Intelligence in Education

    Open Access•Ido Roll, Ruth Wylie•International Journal of…•2016

  • Challenges and Future Directions of Big Data and Artificial Intelligence in Education

    Open Access•Hui Luan, Peter Geczy et al.•Frontiers in Psychology•2020

  • Application and theory gaps during the rise of Artificial Intelligence in Education

    Open Access•Xieling Chen, Haoran Xie et al.•Computers and Education:…•2020

  • Different Bodies, Different Minds

    Open Access•Daniel Casasanto•Current Directions in Psychological…•2011

  • Hey Alexa … examine the variables influencing the use of artificial intelligent in-home voice assistants

    Open Access•Graeme McLean, Kofi Osei-Frimpong•Computers in Human Behavior•2019

  • Artificial Intelligence trends in education

    Open Access•Maud Chassignol, Aleksandr Khoroshavin et al.•Procedia Computer Science•2018

  • High-performance medicine

    Open Access•Eric J Topol•Nature Medicine•2019

  • Deep learning

    Open Access•Yann LeCun, Yoshua Bengio et al.•Nature•2015

  • Handbook of Qualitative Organizational Research

    Roderick Moreland Kramer, Kimberly D Elsbach et al.•Handbook of Qualitative…•2015

  • Comparative Study of the Attitudes and Perceptions of University Students in Business Administration and Management and in Education toward Artificial Intelligence

    Open Access•Cristina Almaraz-López, Fernando Almaraz-Menéndez et al.•Education Sciences•2023

  • A bibliometric analysis of worldwide educational artificial intelligence research development in recent twenty years

    Open Access•Pu Song, Xiang Wang•Asia Pacific Education Review•2020

  • A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education

    Open Access•Qi Xia, Thomas K F Chiu et al.•Computers & Education•2022

  • Exploring EFL university teachers’ beliefs in integrating ChatGPT and other large language models in language education

    Y Gao, Qikai Wang et al.•Asia Pacific Journal of Education•2024

  • The Effects of Using AI Tools on Critical Thinking in English Literature Classes Among EFL Learners

    Open Access•Wenxia Liu, Yunsong Wang•European Journal of Education•2024

  • Fostering Engagement in AI ‐Mediate Chinese EFL Classrooms

    Open Access•Xiaochen Wang, Y Gao et al.•European Journal of Education•2025

  • Modelling Generative AI Acceptance, Perceived Teachers' Enthusiasm and Self‐Efficacy to English as a Foreign Language Learners' Well‐Being in the Digital Era

    Open Access•Fangwei Huang, Yongliang Wang et al.•European Journal of Education•2024

  • The Contribution of Teacher Self‐Efficacy, Resilience and Emotion Regulation to Teachers' Well‐Being

    Open Access•Lihua Lu, Cuiying Wang et al.•European Journal of Education•2024

  • Artificial intelligence in fiction

    Open Access•Isabella Hermann•AI & Society•2023

  • Understanding Medical Students’ Perceptions of and Behavioral Intentions toward Learning Artificial Intelligence

    Open Access•Xin Li, Michael Yi-Chao Jiang et al.•International Journal of…•2022

  • A Holistic Approach to the Design of Artificial Intelligence (AI) Education for K-12 Schools

    Open Access•Thomas K F Chiu•TechTrends•2021

  • Understanding visual metaphor

    Open Access•Elisabeth El Refaie•Visual Communication•2003

  • Gender stereotypes of women in television advertising in Ukraine

    Mariana Kitsa, Iryna Mudra•Feminist Media Studies•2019

  • Mirror, Mirror on the Wall

    Open Access•Zara Ersozlu, Zehra Nur Ersozlu•The Anthropologist•2013

  • Using students’ drawings to elicit general and special educators’ perceptions of co-teaching

    Open Access•Harriet J Bessette•Teaching and Teacher Education•2007

  • Clashing metaphors about classroom teachers

    Open Access•Rebecca L Oxford, Stephen Tomlinson et al.•System•1998

  • Engagement and willingness to communicate in the L2 classroom

    Yongliang Wang, Hanwei Wu et al.•Journal of Multilingual and…•2025

  • Qualitative Data Analysis

    Open Access•Matthew B Miles, A Michael Huberman•Journal of Environmental Psychology•1994

  • Evaluating Conceptual Metaphor Theory

    Raymond W Gibbs•Discourse Processes•2011

Unique citing works7
Citations per year7
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 7

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae